DepthAI Python API utilities, examples, and tutorials.
This repo contains demo application, which can load different networks, create pipelines, record video, etc.
Documentation is available at https://docs.luxonis.com.
python3 -m pip install -U pip)
Optional: For command line autocomplete when pressing TAB, only bash interpreter supported now: Add to .bashrc:
echo 'eval "$(register-python-argcomplete depthai_demo.py)"' >> ~/.bashrc
If you use any other interpreter: https://kislyuk.github.io/argcomplete/
python3 depthai_demo.py- depth & CNN inference example
OpenVINO toolkit contains components which allow conversion of existing supported trained
Tensorflowmodels into Intel Movidius binary format through the Intermediate Representation (IR) format.
Example of the conversion: 1. First the
model_optimizertool will convert the model to IR format:
cd /deployment_tools/model_optimizer python3 mo.py --model_name ResNet50 --output_dir ResNet50_IR_FP16 --framework tf --data_type FP16 --input_model inference_graph.pb
ResNet50.bin- weights file;
ResNet50.xml- execution graph for the network;
ResNet50.mapping- mapping between layers in original public/custom model and layers within IR.
The weights (
.bin) and graph (
.xml) files produced above (or from the Intel Model Zoo) will be required for building a blob file, with the help of the
myriad_compiletool. When producing blobs, the following constraints must be applied:
CMX-SLICES = 4 SHAVES = 4 INPUT-FORMATS = 8 OUTPUT-FORMATS = FP16/FP32 (host code for meta frame display should be updated accordingly)
Example of command execution:
/deploymenttools/inferenceengine/lib/intel64/myriadcompile -m ./ResNet50.xml -o ResNet50.blob -ip U8 -VPUMYRIADPLATFORM VPUMYRIAD2480 -VPUNUMBEROFSHAVES 4 -VPUNUMBEROFCMXSLICES 4
We are actively developing the DepthAI framework, and it's crucial for us to know what kind of problems you are facing.
If you run into a problem, please follow the steps below and email [email protected]:
log_system_information.shand share the output from (